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import os
from fastapi import FastAPI
from dotenv import load_dotenv
from huggingface_hub.inference._mcp.agent import Agent
import gradio as gr
import uvicorn
from fastapi.responses import RedirectResponse
from fastapi.middleware.cors import CORSMiddleware
from typing import Optional, Literal
load_dotenv()
HF_TOKEN=os.getenv("HF_TOKEN")
HF_MODEL=os.getenv("HF_MODEL","Qwen/Qwen1.5-0.5B-Chat")
app=FastAPI(title="MODEL-CARD-CHATBOT")
app.add_middleware(CORSMiddleware,allow_origins=["*"],allow_methods=["*"],allow_header=["*"])
agent_instance: Optional[Agent]=None
DEFAULT_PROVIDER:Literal['hf-inference']="hf-inference"
async def get_agent():
"""Get or create the agent instance."""
global agent_instance
if agent_instance is None and HF_TOKEN:
print("🔧 Creating new Agent instance ...")
print(f"✅ HF_TOKEN present : {bool(HF_TOKEN)}")
print(f"🤖 Model: {HF_MODEL}")
print(f"Provider: {DEFAULT_PROVIDER}")
try:
agent=Agent(model=HF_MODEL,provider="hf-inference",api_key=HF_TOKEN,
servers=[{"type":"stdio","config":{
"command":"python",
"args":["mcp_server.py"],"cwd":".","env":{"HF_TOKEN": HF_TOKEN} if HF_TOKEN else {}}}])
print("🚀 Agent instance created successfully")
print("🔁 loading tools ...")
await agent_instance.load_tools()
print("✅ Tools loaded successfully")
except Exception as e:
print(f"❌ Error creating/loading agent: {str(e)}")
return agent_instance
@app.on_event("startup")
async def startup_event():
global agent_instance
agent_instance = await get_agent()
def chat_function(user_message,history,model_id):
"""Handles a user question by prompting the agent to read a model card and answer.
Args:
user_message (str): The user's question.
history (list): Chat history for display.
model_id (str): Hugging Face repo ID
Returns:
Tuple[list,str]: Updated Chat history and empty string for clearing input."""
prompt=f"""You're an assistant helping with hugging face model cards.
First, run the tool `read_model_card` on repo_id `{model_id}` to get the model card.
Then answer this user question based on the model card:
User question: {user_message}"""
history=history+[(user_message,None)]
try:
response=""
for output in agent_instance.run(prompt):
if hasattr(output,"content") and output.content:
response=output.content
final_response=response or "⚠️ Sorry, I couldn't generate a response."
history[-1]=(user_message,final_response)
except Exception as e:
history[-1]=(user_message,f"⚠️ Error: {str(e)}")
return history, ""
def create_gradio_app():
with gr.Blocks(title="Model Card Chatbot") as demo:
gr.Markdown("## 🤖 Model Card Chatbot\nAsk questions about Hugging Face model card")
with gr.Row():
model_id=gr.Textbox(label="MODEL ID", value="google/gemma-2-2b")
user_input=gr.Textbox(label="Your Question",value="Ask something about the model card .....")
chat=gr.Chatbot(label="chat")
send=gr.Button("Ask")
send.click(fn=chat_function,inputs=[user_input,chat,model_id],outputs=[chat,user_input])
return demo
gradio_app=create_gradio_app()
app=gr.mount_gradio_app(app,gradio_app,path="/")
@app.get("/")
async def root():
return RedirectResponse("/")
if __name__=="__main__":
uvicorn.run("app:app",host="0.0.0.0",port=7860,reload=True)
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